Journal of Toxicology and Environmental Health, Part A, 78:524–533, 2015 Copyright © Taylor & Francis Group, LLC ISSN: 1528-7394 print / 1087-2620 online DOI: 10.1080/15287394.2014.991053
THE AIR QUALITY HEALTH INDEX AND EMERGENCY DEPARTMENT VISITS FOR URTICARIA IN WINDSOR, CANADA Termeh Kousha1, Giuseppe Valacchi2 1 2
Department of Mathematics and Statistics, University of Ottawa, Ottawa, Ontario, Canada Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
Ambient air pollution exposure has been associated with several health conditions, limited not only to respiratory and cardiovascular systems but also to cutaneous tissues. However, few epidemiological studies examined pollution exposure on skin problems. Basically, the common mechanism by which pollution may affect skin physiology is by induction of oxidative stress and inflammation. Urticaria is among the skin pathologies that have been associated with pollution. Based on the combined effects of three ambient air pollutants, ozone (O3 ), nitrogen dioxide (NO2 ), and fine particulate matter (PM) with a median aerodynamic diameter of less than 2.5 µm (PM 2.5 ), on mortality, the Air Quality Health Index (AQHI) in Canada was developed. The aim of this study was to examine the associations of short-term changes in AQHI with emergency department (ED) visits for urticaria in Windsor-area hospitals in Canada. Diagnosed ED visits were retrieved from the National Ambulatory Care Reporting System (NACRS). A time-stratified case-crossover design was applied to 2905 ED visits (males = 1215; females = 1690) for urticaria from April 2004 through December 2010. Odds ratios (OR) and their corresponding 95% confidence intervals (95%CI) for ED visits associated with increase by one unit of risk index were calculated employing conditional logistic regression. Positive and significant results were observed between AQHI levels and OR for ED visits for urticaria in Windsor for lags 2 and 3 days. A distributed lag nonlinear model technique was applied to daily counts of ED visits for lags 0 to 10 and significant results were obtained from lag 2 to lag 5 and for lag 9. These findings demonstrated associations between ambient air pollution and urticarial confirming that air pollution affects skin conditions.
Urticaria, commonly referred to as hives, is the most frequent dermatologic disorder seen in the emergency department (ED) (BallmerWeber et al., 2010). Urticaria is a red, raised, itchy skin rash that is often triggered by something that produces an allergic reaction—an allergen, but it may also be idiopathic. The role of ROS in urticarial pathogenesis was previously demonstrated by Kalkan et al. (2014). Many studies confirmed the effects of pollutants such as O3 on the respiratory tract (Mustafa, 1990; Kousha et al., 2014; Szyszkowicz et al., 2014), and also on cutaneous tissues (Cotovio et al., 2001; Larrieu
Living organisms are continuously exposed to environmental pollutants by ingestion, inhalation or skin contact. Because the skin is an interface between the body and the environment, it is chronically exposed to several forms of stressors such as ultraviolet (UV) irradiation and other environmental oxidants such as nitric oxide (NO), particulate matter (PM), and ozone (O3 ). Many environmental pollutants are either themselves oxidants or catalyze the production of reactive oxygen species (ROS) directly or indirectly (Ghio et al., 2012); therefore, ROS may be involved in the pathogenesis of several skin disorders including urticaria.
Received 28 October 2014; accepted 19 November 2014. Address correspondence to Prof. Giuseppe Valacchi, Department of Life Sciences and Biotechnology, University of Ferrara, Via Borsari, 46, 44121 Ferrara, Italy. E-mail: [email protected] 524
POLLUTION EXPOSURE AFFECTS SKIN PHYSIOLOGY
et al., 2009; Packer and Valacchi, 2002; Szyszkowicz et al., 2010; Thiele et al., 1997; Sticozzi et al., 2012). It is widely known that some gases such as O3 , carbon monoxide (CO), NO, and carbon dioxide (CO2 ) behave both as useful and as harmful agents (Valacchi et al., 2005). Indeed, several studies reported that O3 adversely affects health (Fridovich, 1978; Aris et al., 1993; Pryor, 1993; Camhi et al., 1995; Devlin et al., 1997; Bhalla, 1999; Morrison et al, 2006) and is a risk factor for respiratory conditions such as asthma (Burnett et al., 2001; Villeneuve et al., 2007; Stieb et al., 2009) and airway hyperactivity (Larsen et al., 2010). There have been also a number of investigations that linked ambient O3 to cardiac disease (Stieb et al., 2009; Wong et al., 1999; Beckerman et al., 2012; Almeida et al., 2014), appendicitis (Kaplan et al., 2009), headaches, migraines (Szyszkowicz et al., 2009; Dales et al., 2009), epistaxis (Szyszkowicz et al., 2014), and cellulitis (Szyszkowicz et al., 2010). In addition, Valacchi et al. (2005) determined the effect of 0.8 ppm O3 on both skin and lung tissues using the same experimental SKH1 murine animal model. Further, Valacchi et al. (2004, 2012) showed that O3 in cutaneous tissues depletes antioxidant content in the stratum corneum, leading to a cascade of effects even in the deeper layers of the skin. Of note is the recent study by Xu et al. (2011) that reported a significant association between ambient O3 and ED visits for skin conditions (urticaria, eczema, contact dermatitis, rash/other nonspecific eruption, and infected skin disease) in an analysis of almost 70,000 patient visits to a single hospital over almost 2 years by residents of urban areas of Shanghai. There are also investigations providing evidence that ambient PM affects skin physiology. Vierkötter and coworkers (2010) noted the effects of exposure to PM on extrinsic skin aging by using a cross-sectional design. In a joint initiative beginning in 2001, Health Canada and Environment Canada proceeded to develop a new air-health index, the Air Quality Health Index (AQHI), to scale health risks in relation to ambient air pollutant concentrations. The AQHI is based upon the combined effects on mortality of three ambient
525
air pollutants: O3 , NO2 , and fine PM with a diameter less than 2.5 µm (PM2.5 ). The aim of the present study was to investigate correlations between AQHI as an exposure measurement and ED visits for urticaria in Windsor, Canada. Associations of short-term changes in the daily mean of AQHI with ED visits were examined for urticaria identified using the International Classification of Diseases 10th revision (ICD10): code L50. In addition, calculated odds ratio (OR) for the daily maximum of AQHI was determined for combined effects and separately for the three individual components pollutants (O3, NO2 , and PM25 ). Further, AQHI for two other ambient air pollutants, carbon monoxide (CO) and sulfur dioxide (SO2 ) was also measured. MATERIALS AND METHODS Associations of short-term changes in the AQHI with ED visits were examined for urticaria in Windsor-area hospitals. Diagnosed ED visits were retrieved from the National Ambulatory Care Reporting System (NACRS). The study sample included all patients served by hospitals in Windsor, between April 1, 2004, and December 31, 2010, and used the three first characters of the postal code of each patient’s home address to identify persons living in Windsor. The AQHI values are presented on a continuous scale of 1–10. To improve public comprehension the scale was divided as follows: 1–3 = low risk, 4–6 = moderate risk, 7–10 = high risk, and very high risk when greater than 10. The AQHI values are calculated according to following formula, which was originally presented in the publication on the definition and characteristics of this index (Stieb et al., 2008): AQHI = 10/10.4 × 100 × (exp(0.000871 × NO2 ) + exp(0.000537 × O3 ) + exp(0.000487 × PM2.5 ) − 3) The exp(x) is an exponential function. This quantity was used to represent the level of
526
T. KOUSHA AND G. VALACCHI
exposure or health risk. The AQHI incorporates 24 values daily. The daily average of these 24 values of the AQHI was used to represent the value for a specific day in our calculations. Similar calculations were also performed using the daily maximum value of the AQHI. Since for the time period of the study data for two other air pollutants (CO and SO2 ) were available from Environment Canada, our analysis for these pollutants was also performed, which allows one to see effects of air pollution not included in the AQHI calculation.
Statistical Analysis Case-crossover (CC) design was applied for this cross-sectional type of data (Janes et al., 2005). The CC technique is an adaptation and realization of the case-control study (Maclure, 1991). In the CC method, cases act as their own controls on a set of predefined control days proximate to the time they became cases. In order to produce unbiased conditional logistic regression estimates, a time-stratified approach was applied to determine controls (Janes et al., 2005). In the design, controls are matched to case periods by day of week for the case period (day) in that the control periods are determined as other days in the same month and year. Using this strategy, three or four controls are presented for each case, with affected individuals serving as their own controls. By design, this type of case control compensates for local time-invariant factors such as health or social status. The day on which the exposure supposedly affected the subject’s health is considered the case day. Ambient temperature and relative humidity factors were used in form of natural splines with four degrees of freedom. The concept of lag time was incorporated into their exposure definition, that is, the time between air pollutant measurement and exposure-response relationships between exposure to air pollutants and ED visit for urticaria. All components, air pollutants and meteorological factors, in the models were lagged by the same number of days, from 0
(same day visit) to 10. Air pollutant concentrations, temperature and relative humidity were expressed as daily mean values. A p value
THE AIR QUALITY HEALTH INDEX AND EMERGENCY DEPARTMENT VISITS FOR URTICARIA IN WINDSOR, CANADA Termeh Kousha1, Giuseppe Valacchi2 1 2
Department of Mathematics and Statistics, University of Ottawa, Ottawa, Ontario, Canada Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
Ambient air pollution exposure has been associated with several health conditions, limited not only to respiratory and cardiovascular systems but also to cutaneous tissues. However, few epidemiological studies examined pollution exposure on skin problems. Basically, the common mechanism by which pollution may affect skin physiology is by induction of oxidative stress and inflammation. Urticaria is among the skin pathologies that have been associated with pollution. Based on the combined effects of three ambient air pollutants, ozone (O3 ), nitrogen dioxide (NO2 ), and fine particulate matter (PM) with a median aerodynamic diameter of less than 2.5 µm (PM 2.5 ), on mortality, the Air Quality Health Index (AQHI) in Canada was developed. The aim of this study was to examine the associations of short-term changes in AQHI with emergency department (ED) visits for urticaria in Windsor-area hospitals in Canada. Diagnosed ED visits were retrieved from the National Ambulatory Care Reporting System (NACRS). A time-stratified case-crossover design was applied to 2905 ED visits (males = 1215; females = 1690) for urticaria from April 2004 through December 2010. Odds ratios (OR) and their corresponding 95% confidence intervals (95%CI) for ED visits associated with increase by one unit of risk index were calculated employing conditional logistic regression. Positive and significant results were observed between AQHI levels and OR for ED visits for urticaria in Windsor for lags 2 and 3 days. A distributed lag nonlinear model technique was applied to daily counts of ED visits for lags 0 to 10 and significant results were obtained from lag 2 to lag 5 and for lag 9. These findings demonstrated associations between ambient air pollution and urticarial confirming that air pollution affects skin conditions.
Urticaria, commonly referred to as hives, is the most frequent dermatologic disorder seen in the emergency department (ED) (BallmerWeber et al., 2010). Urticaria is a red, raised, itchy skin rash that is often triggered by something that produces an allergic reaction—an allergen, but it may also be idiopathic. The role of ROS in urticarial pathogenesis was previously demonstrated by Kalkan et al. (2014). Many studies confirmed the effects of pollutants such as O3 on the respiratory tract (Mustafa, 1990; Kousha et al., 2014; Szyszkowicz et al., 2014), and also on cutaneous tissues (Cotovio et al., 2001; Larrieu
Living organisms are continuously exposed to environmental pollutants by ingestion, inhalation or skin contact. Because the skin is an interface between the body and the environment, it is chronically exposed to several forms of stressors such as ultraviolet (UV) irradiation and other environmental oxidants such as nitric oxide (NO), particulate matter (PM), and ozone (O3 ). Many environmental pollutants are either themselves oxidants or catalyze the production of reactive oxygen species (ROS) directly or indirectly (Ghio et al., 2012); therefore, ROS may be involved in the pathogenesis of several skin disorders including urticaria.
Received 28 October 2014; accepted 19 November 2014. Address correspondence to Prof. Giuseppe Valacchi, Department of Life Sciences and Biotechnology, University of Ferrara, Via Borsari, 46, 44121 Ferrara, Italy. E-mail: [email protected] 524
POLLUTION EXPOSURE AFFECTS SKIN PHYSIOLOGY
et al., 2009; Packer and Valacchi, 2002; Szyszkowicz et al., 2010; Thiele et al., 1997; Sticozzi et al., 2012). It is widely known that some gases such as O3 , carbon monoxide (CO), NO, and carbon dioxide (CO2 ) behave both as useful and as harmful agents (Valacchi et al., 2005). Indeed, several studies reported that O3 adversely affects health (Fridovich, 1978; Aris et al., 1993; Pryor, 1993; Camhi et al., 1995; Devlin et al., 1997; Bhalla, 1999; Morrison et al, 2006) and is a risk factor for respiratory conditions such as asthma (Burnett et al., 2001; Villeneuve et al., 2007; Stieb et al., 2009) and airway hyperactivity (Larsen et al., 2010). There have been also a number of investigations that linked ambient O3 to cardiac disease (Stieb et al., 2009; Wong et al., 1999; Beckerman et al., 2012; Almeida et al., 2014), appendicitis (Kaplan et al., 2009), headaches, migraines (Szyszkowicz et al., 2009; Dales et al., 2009), epistaxis (Szyszkowicz et al., 2014), and cellulitis (Szyszkowicz et al., 2010). In addition, Valacchi et al. (2005) determined the effect of 0.8 ppm O3 on both skin and lung tissues using the same experimental SKH1 murine animal model. Further, Valacchi et al. (2004, 2012) showed that O3 in cutaneous tissues depletes antioxidant content in the stratum corneum, leading to a cascade of effects even in the deeper layers of the skin. Of note is the recent study by Xu et al. (2011) that reported a significant association between ambient O3 and ED visits for skin conditions (urticaria, eczema, contact dermatitis, rash/other nonspecific eruption, and infected skin disease) in an analysis of almost 70,000 patient visits to a single hospital over almost 2 years by residents of urban areas of Shanghai. There are also investigations providing evidence that ambient PM affects skin physiology. Vierkötter and coworkers (2010) noted the effects of exposure to PM on extrinsic skin aging by using a cross-sectional design. In a joint initiative beginning in 2001, Health Canada and Environment Canada proceeded to develop a new air-health index, the Air Quality Health Index (AQHI), to scale health risks in relation to ambient air pollutant concentrations. The AQHI is based upon the combined effects on mortality of three ambient
525
air pollutants: O3 , NO2 , and fine PM with a diameter less than 2.5 µm (PM2.5 ). The aim of the present study was to investigate correlations between AQHI as an exposure measurement and ED visits for urticaria in Windsor, Canada. Associations of short-term changes in the daily mean of AQHI with ED visits were examined for urticaria identified using the International Classification of Diseases 10th revision (ICD10): code L50. In addition, calculated odds ratio (OR) for the daily maximum of AQHI was determined for combined effects and separately for the three individual components pollutants (O3, NO2 , and PM25 ). Further, AQHI for two other ambient air pollutants, carbon monoxide (CO) and sulfur dioxide (SO2 ) was also measured. MATERIALS AND METHODS Associations of short-term changes in the AQHI with ED visits were examined for urticaria in Windsor-area hospitals. Diagnosed ED visits were retrieved from the National Ambulatory Care Reporting System (NACRS). The study sample included all patients served by hospitals in Windsor, between April 1, 2004, and December 31, 2010, and used the three first characters of the postal code of each patient’s home address to identify persons living in Windsor. The AQHI values are presented on a continuous scale of 1–10. To improve public comprehension the scale was divided as follows: 1–3 = low risk, 4–6 = moderate risk, 7–10 = high risk, and very high risk when greater than 10. The AQHI values are calculated according to following formula, which was originally presented in the publication on the definition and characteristics of this index (Stieb et al., 2008): AQHI = 10/10.4 × 100 × (exp(0.000871 × NO2 ) + exp(0.000537 × O3 ) + exp(0.000487 × PM2.5 ) − 3) The exp(x) is an exponential function. This quantity was used to represent the level of
526
T. KOUSHA AND G. VALACCHI
exposure or health risk. The AQHI incorporates 24 values daily. The daily average of these 24 values of the AQHI was used to represent the value for a specific day in our calculations. Similar calculations were also performed using the daily maximum value of the AQHI. Since for the time period of the study data for two other air pollutants (CO and SO2 ) were available from Environment Canada, our analysis for these pollutants was also performed, which allows one to see effects of air pollution not included in the AQHI calculation.
Statistical Analysis Case-crossover (CC) design was applied for this cross-sectional type of data (Janes et al., 2005). The CC technique is an adaptation and realization of the case-control study (Maclure, 1991). In the CC method, cases act as their own controls on a set of predefined control days proximate to the time they became cases. In order to produce unbiased conditional logistic regression estimates, a time-stratified approach was applied to determine controls (Janes et al., 2005). In the design, controls are matched to case periods by day of week for the case period (day) in that the control periods are determined as other days in the same month and year. Using this strategy, three or four controls are presented for each case, with affected individuals serving as their own controls. By design, this type of case control compensates for local time-invariant factors such as health or social status. The day on which the exposure supposedly affected the subject’s health is considered the case day. Ambient temperature and relative humidity factors were used in form of natural splines with four degrees of freedom. The concept of lag time was incorporated into their exposure definition, that is, the time between air pollutant measurement and exposure-response relationships between exposure to air pollutants and ED visit for urticaria. All components, air pollutants and meteorological factors, in the models were lagged by the same number of days, from 0
(same day visit) to 10. Air pollutant concentrations, temperature and relative humidity were expressed as daily mean values. A p value
